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Maximilian Stubbemann
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2020 – today
- 2024
- [i11]Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme:
Moco: A Learnable Meta Optimizer for Combinatorial Optimization. CoRR abs/2402.04915 (2024) - [i10]Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme:
ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. CoRR abs/2403.03812 (2024) - [i9]Tobias Hille, Maximilian Stubbemann, Tom Hanika:
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research. CoRR abs/2403.08438 (2024) - [i8]Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme:
Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training. CoRR abs/2404.06966 (2024) - [i7]Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme:
Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting. CoRR abs/2405.03582 (2024) - 2023
- [b1]Maximilian Stubbemann:
Orometry, intrinsic dimensionality and learning: Novel insights into network data. University of Kassel, Germany, 2023 - [j2]Maximilian Stubbemann, Tom Hanika
, Friedrich Martin Schneider:
Intrinsic Dimension for Large-Scale Geometric Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c3]Maximilian Stubbemann
, Gerd Stumme
:
The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks. ECML/PKDD (3) 2023: 177-192 - [i6]Maximilian Stubbemann, Tobias Hille, Tom Hanika:
Selecting Features by their Resilience to the Curse of Dimensionality. CoRR abs/2304.02455 (2023) - 2022
- [c2]Maximilian Stubbemann
, Gerd Stumme
:
LG4AV: Combining Language Models and Graph Neural Networks for Author Verification. IDA 2022: 315-326 - [p1]Dominik Dürrschnabel, Tom Hanika
, Maximilian Stubbemann:
FCA2VEC: Embedding Techniques for Formal Concept Analysis. Complex Data Analytics with Formal Concept Analysis 2022: 47-74 - [i5]Maximilian Stubbemann, Tom Hanika, Friedrich Martin Schneider:
Intrinsic Dimension for Large-Scale Geometric Learning. CoRR abs/2210.05301 (2022) - 2021
- [j1]Tobias Koopmann
, Maximilian Stubbemann, Matthias Kapa, Michael Paris
, Guido Buenstorf, Tom Hanika
, Andreas Hotho, Robert Jäschke, Gerd Stumme:
Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research. Scientometrics 126(12): 9847-9868 (2021) - [i4]Maximilian Stubbemann, Gerd Stumme:
LG4AV: Combining Language Models and Graph Neural Networks for Author Verification. CoRR abs/2109.01479 (2021) - [i3]Maximilian Stubbemann, Gerd Stumme:
The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks. CoRR abs/2110.13774 (2021) - 2020
- [c1]Maximilian Stubbemann
, Tom Hanika
, Gerd Stumme
:
Orometric Methods in Bounded Metric Data. IDA 2020: 496-508
2010 – 2019
- 2019
- [i2]Maximilian Stubbemann, Tom Hanika, Gerd Stumme:
Orometric Methods in Bounded Metric Data. CoRR abs/1907.09239 (2019) - [i1]Dominik Dürrschnabel
, Tom Hanika, Maximilian Stubbemann:
FCA2VEC: Embedding Techniques for Formal Concept Analysis. CoRR abs/1911.11496 (2019)
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last updated on 2024-06-10 20:27 CEST by the dblp team
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